Determination of Vickers hardness in D2 steel and TiNbN coating using convolutional neural networks
The study of material hardness is crucial for determining its quality, potential failures, and appropriate applications, as well as minimizing losses incurred during the production process. To achieve this, certain criteria must be met to ensure high quality. This process is typically performed manu...
- Autores:
-
Buitrago Diaz, Juan C.
Ortega-Portilla, Carolina
Mambuscay, Claudia L.
Piamba, Jeferson Fernando
Forero, Manuel G.
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2023
- Institución:
- Universidad de Ibagué
- Repositorio:
- Repositorio Universidad de Ibagué
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unibague.edu.co:20.500.12313/3843
- Acceso en línea:
- https://hdl.handle.net/20.500.12313/3843
- Palabra clave:
- Material hardness
Indentation image analysis
Vickers hardness
Corner detection
Diagonal measurement
D2 steel
Thermal treatment
Titanium niobium nitride (TiNbN) coating
- Rights
- openAccess
- License
- http://purl.org/coar/access_right/c_abf2